# deepseek-v4p1-flash-1017 Usage, Cost & Rank | OpenCode Data

> deepseek-v4p1-flash-1017 ranked #41 by tokens across OpenCode last week, with 0% of tokens over the past two months.

- Page: https://opencode.ai/data/deepseek/deepseek-v4p1-flash-1017
- JSON: https://opencode.ai/data/deepseek/deepseek-v4p1-flash-1017.json
- Model ID: deepseek-v4p1-flash-1017
- Lab: DeepSeek
- Updated: 2026-11-07T06:12:27.000Z

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #41 |
| Tokens | 2.5B |
| Share of all tokens | 0% |
| Change vs previous 2 months | +100% |
| Unique users | 233 |
| Completed sessions | 2,181 |
| Average tokens per session | 1.1M |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 85.4% |
| Weekly retention | - |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-11-07 | 2.5B | 233 | 2,181 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | India | 500M | 19% |
| 2 | United States | 300M | 10.3% |
| 3 | China | 200M | 8.3% |
| 4 | Russia | 200M | 6.9% |
| 5 | Indonesia | 200M | 6.3% |
| 6 | Mexico | 100M | 2.7% |
| 7 | Brazil | 100M | 2.5% |
| 8 | Canada | 100M | 2.2% |
| 9 | Vietnam | 100M | 2% |
| 10 | Philippines | 0 | 1.8% |
| 11 | Pakistan | 0 | 1.7% |
| 12 | Japan | 0 | 1.6% |
| 13 | Kazakhstan | 0 | 1.5% |
| 14 | Germany | 0 | 1.4% |
| 15 | Australia | 0 | 1.4% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 37 | [grok-4.7](https://opencode.ai/data/xai/grok-4-7.md) | xAI | 14B |
| 38 | [hy4-preview](https://opencode.ai/data/tencent/hy4-preview.md) | Tencent | 11B |
| 39 | [step-5-preview](https://opencode.ai/data/stepfun/step-5-preview.md) | StepFun | 6.7B |
| 40 | [jev-1.13](https://opencode.ai/data/unknown/jev-1-13.md) | - | 4.9B |
| 41 | [deepseek-v4p1-flash-1017](https://opencode.ai/data/deepseek/deepseek-v4p1-flash-1017.md) | DeepSeek | 2.5B |
| 42 | [gpt-5-nano](https://opencode.ai/data/openai/gpt-5-nano.md) | OpenAI | 194M |
| 43 | [z-ai/glm-5.3-flash](https://opencode.ai/data/zhipu/z-ai-glm-5-3-flash.md) | Zhipu | 15M |
| 44 | [dungcsnd113/deepseek-v4.1-flash-1017](https://opencode.ai/data/deepseek/dungcsnd113-deepseek-v4-1-flash-1017.md) | DeepSeek | 15M |
| 45 | [deepseek-v4-flash](https://opencode.ai/data/deepseek/deepseek-v4-flash.md) | DeepSeek | 14M |
| 46 | [qiniu/conatus](https://opencode.ai/data/custom/qiniu-conatus.md) | Custom | 3.9M |

## Methodology

- Updates: Aggregated every hour. Days and weeks use UTC.
- Tokens: Input, output, reasoning, and cached tokens for each request.
- Users and sessions: Approximate counts of distinct users and OpenCode sessions.
- Cost: Session cost is the average cost per OpenCode session. Token prices are list prices from the OpenCode model catalog.
- Retention: The share of a model's users in one week who use it again the next week.
- Citation: Cite OpenCode Data (opencode.ai/data) with the update time shown at the top of the page.